Talking to Cancer Patients about Complementary Therapies: Is It the Physician’s Responsibility?
Bibliographic record
Abstract
BACKGROUND: To ensure the safety and effectiveness of cancer management, it is important for physicians treating cancer patients to know whether their patients are using complementary and alternative medicine (CAM) and if so, why. OBJECTIVE: Here, we discuss the ethical and legal obligations of physicians to discuss cam use in an oncology setting, and we provide practical advice on how patient-provider communication about cam can be improved. RESULTS: Physicians have both ethical and legal obligations to their patients, including the obligation to respect patient autonomy. This latter obligation extends to use of CAM by patients and needs to be addressed beginning early in the patient-provider relationship. Because lack of education in this field and lack of time during patient consultations are barriers to talking with patients about cam, we provide resources to facilitate such discussions. These resources include suggestions on how to discuss the topic of cam and a wide range of information sources. CONCLUSIONS: Discussing CAM with patients is the physician's responsibility, and such discussion will facilitate evidence-based, patient-centred cancer care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".